AI RESEARCH
AmbiSQL: Interactive Ambiguity Detection and Resolution for Text-to-SQL
arXiv CS.CL
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ArXi:2508.15276v2 Announce Type: replace-cross Text-to-SQL systems translate natural language questions into SQL queries, providing substantial value for non-expert users. While large language models (LLMs) show promising results for this task, they remain error-prone. Query ambiguity has been recognized as a major obstacle in LLM-based Text-to-SQL systems, leading to misinterpretation of user intent and inaccurate SQL generation.